Google Reliability Engineer, Process Reliability, Self-Driving Car, X in Mountain View, California
The self-driving car project aims to improve people’s lives by transforming mobility and making it easier and safer for everyone to get around, regardless of their ability to drive. So far, we’ve self-driven over 1 million miles and are currently out on the streets of Mountain View, California and Austin, Texas.
In this role, you will manage the PFMEAs, process validation activities and supplier assessments of custom driverless vehicle hardware. You have a broad technical background with the ability to work with product design engineers, manufacturing engineers and supplier quality engineers to manage all reliability development and testing activities on the manufacturing side. Strong interpersonal and communication skills are an absolute requirement to establish effective working relationships within and outside of Google.
- Facilitate PFMEAs and implement the action items.
- Develop and execute process validation plans, burn-in plans, and ongoing reliability test plans.
- Drive the root-cause analysis and failure mitigation process of manufacturing defects and field returns.
- Monitor reliability related manufacturing performance metrics.
- Perform supplier assessments and visits with focus on reliability performance.
- BS degree in an engineering field or equivalent practical experience.
- 5 years of manufacturing experience and 3 years of experience in a Reliability Engineering or Quality Engineering role.
- Experience using manufacturing quality and reliability techniques including PFMEA, Process Flow Diagrams, Control Plans, Process Validation.
- Experience with strain gage measurements as well as applying quality standards including ISO 16949, AEC-Q, and IEC-610. Ability to travel domestically and internationally.
- Master’s degree in an engineering field with 3 years of manufacturing experience and 2 years in a Reliability Engineering or Quality Engineering role.
- Automotive or Aerospace experience.
- Statistical analysis experience including Monte Carlo Analysis, DoE, SPC, Gauge R&R.;
- Understanding of physics of failure.
- Excellent sense of humor and probing skills.
- Excellent oral, written and presentation communication skills.